68 citations · 320 across the 15 of their papers we have counts for
16 papers
SeGraM: A Universal Hardware Accelerator for Genomic Sequence-to-Graph and Sequence-to-Sequence Mapping
Damla Senol Cali, Konstantinos Kanellopoulos, Joel Lindegger +15
A critical step of genome sequence analysis is the mapping of sequenced DNA fragments (i.e., reads) collected from an individual to a known linear reference genome sequence (i.e.,…
Sibyl: Adaptive and Extensible Data Placement in Hybrid Storage Systems Using Online Reinforcement Learning
Gagandeep Singh, Rakesh Nadig, Jisung Park +7
Hybrid storage systems (HSS) use multiple different storage devices to provide high and scalable storage capacity at high performance. Recent research proposes various techniques t…
Algorithmic Improvement and GPU Acceleration of the GenASM Algorithm
Joël Lindegger, Damla Senol Cali, Mohammed Alser +2
We improve on GenASM, a recent algorithm for genomic sequence alignment, by significantly reducing its memory footprint and bandwidth requirement. Our algorithmic improvements redu…
SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems
Christina Giannoula, Ivan Fernandez, Juan Gómez-Luna +3
Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks a…
Casper: Accelerating Stencil Computation using Near-cache Processing
Alain Denzler, Rahul Bera, Nastaran Hajinazar +4
Stencil computation is one of the most used kernels in a wide variety of scientific applications, ranging from large-scale weather prediction to solving partial differential equati…
Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware
Juan Gómez-Luna, Izzat El Hajj, Ivan Fernandez +3
Many modern workloads such as neural network inference and graph processing are fundamentally memory-bound. For such workloads, data movement between memory and CPU cores imposes a…
Accelerating Weather Prediction using Near-Memory Reconfigurable Fabric
Gagandeep Singh, Dionysios Diamantopoulos, Juan Gómez-Luna +4
Ongoing climate change calls for fast and accurate weather and climate modeling. However, when solving large-scale weather prediction simulations, state-of-the-art CPU and GPU impl…
CODIC: A Low-Cost Substrate for Enabling Custom In-DRAM Functionalities and Optimizations
Lois Orosa, Yaohua Wang, Mohammad Sadrosadati +10
DRAM is the dominant main memory technology used in modern computing systems. Computing systems implement a memory controller that interfaces with DRAM via DRAM commands. DRAM exec…
Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecture
Juan Gómez-Luna, Izzat El Hajj, Ivan Fernandez +3
Many modern workloads, such as neural networks, databases, and graph processing, are fundamentally memory-bound. For such workloads, the data movement between main memory and CPU c…
pLUTo: Enabling Massively Parallel Computation in DRAM via Lookup Tables
João Dinis Ferreira, Gabriel Falcao, Juan Gómez-Luna +8
Data movement between the main memory and the processor is a key contributor to execution time and energy consumption in memory-intensive applications. This data movement bottlenec…
SynCron: Efficient Synchronization Support for Near-Data-Processing Architectures
Christina Giannoula, Nandita Vijaykumar, Nikela Papadopoulou +7
Near-Data-Processing (NDP) architectures present a promising way to alleviate data movement costs and can provide significant performance and energy benefits to parallel applicatio…
A Modern Primer on Processing in Memory
Onur Mutlu, Saugata Ghose, Juan Gómez-Luna +3
This paper discusses recent research that aims to enable computation close to data, an approach we broadly call processing-in-memory (PIM). PIM places computation mechanisms in or…
NATSA: A Near-Data Processing Accelerator for Time Series Analysis
Ivan Fernandez, Ricardo Quislant, Christina Giannoula +5
Time series analysis is a key technique for extracting and predicting events in domains as diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and m…
Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores
Orestis Zachariadis, Nitin Satpute, Juan Gómez-Luna +1
Sparse general matrix-matrix multiplication (spGEMM) is an essential component in many scientific and data analytics applications. However, the sparsity pattern of the input matric…
Accelerating B-spline Interpolation on GPUs: Application to Medical Image Registration
Orestis Zachariadis, Andrea Teatini, Nitin Satpute +4
Background and Objective. B-spline interpolation (BSI) is a popular technique in the context of medical imaging due to its adaptability and robustness in 3D object modeling. A fiel…
Dataplant: Enhancing System Security with Low-Cost In-DRAM Value Generation Primitives
Lois Orosa, Yaohua Wang, Ivan Puddu +13
DRAM manufacturers have been prioritizing memory capacity, yield, and bandwidth for years, while trying to keep the design complexity as simple as possible. DRAM chips do not carry…